head to head · open source

Mem0 vs LiteLLM

Mem0 has 65,539 GitHub stars, 7,687 forks, 742 open issues and last shipped yesterday. LiteLLM has 59,036 stars, 11,545 forks, 5,022 open issues and last shipped yesterday. Mem0 leads on adoption by 11% (65,539 vs 59,036 stars). Mem0 is written in Python under Apache-2.0; LiteLLM is written in Python under a custom or non-standard licence. Mem0 has attracted 12% as many forks as stars, LiteLLM 20%. LiteLLM was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

Mem0 ★ 66K LiteLLM ★ 59K category AI & Machine Learning

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Side by side

Mem0 LiteLLM
GitHub stars ★ 66K ★ 59K
License Apache-2.0 Custom / other
Written in Python Python
Last push 2026-09-18 2026-09-18
Forks ⑂ 7.7K ⑂ 12K
Self-hosting Yes Yes
Data ownership Your server Your server

pick Mem0 if

  • You weight community size — 66K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full Mem0 profile →

pick LiteLLM if

  • You want the LiteLLM feature set and don't need the biggest community
  • You prefer the Custom / other license terms
  • Your stack matches Python
  • You evaluated both and LiteLLM fits your workflow better

full LiteLLM profile →

About Mem0

Mem0 is an open source memory layer for AI agents and applications, designed to store, retrieve, and manage persistent context across interactions. It lives in the Python based AI development ecosystem and provides infrastructure that enables agents and apps to remember user preferences, conversation history, and state over time—moving beyond ephemeral chat sessions toward truly adaptive systems.

read the full Mem0 overview →

About LiteLLM

LiteLLM is an open source AI gateway that provides a unified interface to call over 100 large language model (LLM) providers—including OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, Google VertexAI, and vLLM—using the OpenAI compatible API format. It runs as both a Python SDK for direct integration and as a standalone proxy server for centralized, team or organization wide use.

read the full LiteLLM overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K

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openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm hermes-agent vs opencode hermes-agent vs n8n openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all llama-cpp vs vllm

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Mem0 vs Dify Mem0 vs langchain Mem0 vs ponytail Mem0 vs generative-ai-for-beginners Mem0 vs graphify Mem0 vs claude-mem Mem0 vs ragflow Mem0 vs PaddleOCR Mem0 vs Agent-Reach Mem0 vs headroom Mem0 vs daily_stock_analysis Mem0 vs crewAI

Frequently asked questions

Is Mem0 or LiteLLM more popular?

Mem0 has 65,539 GitHub stars and LiteLLM has 59,036. Mem0 has the larger community by that measure.

Are Mem0 and LiteLLM free?

Both are open source. Mem0 is licensed under Apache-2.0, and LiteLLM has no licence declared in this registry. Both are free to self-host.

What is the difference between Mem0 and LiteLLM?

Mem0 is written in Python and LiteLLM in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, Mem0 or LiteLLM?

Choose Mem0 if you want the larger community (65,539 stars) or its Apache-2.0 licence terms. Choose LiteLLM if its feature set, stack or Custom / other licence fits better. Both are self-hostable.